AJR Podcasts: How to Turn Clinical Intuition Into Impactful Science

How to Turn Clinical Intuition Into Impactful Science

Sep 2, 2026

Good research questions may be hiding in everyday clinical work. Marco Francone, MD, PhD, and Daniel Pinto dos Santos, MD, speak with host Amit Gupta, MD, about transforming clinical intuition, recurring gaps, and diagnostic challenges into focused, testable, and clinically impactful research. Listen to their discussion in episode 2 of The Early-Career Researcher’s Playbook, an AJR Podcast Series.

https://www.ajronline.org/doi/10.2214/AJR.26.35769

*Key Takeaways

Questioning the Routine: Meaningful research often begins by simply asking "why" established practices exist. For example, questioning the necessity of a non-contrast series prior to contrast media administration when looking for abdominal hemorrhage may lead to a publishable study.

The Prospective Shift: Retrospective research may be limited by biased intuitions and imperfect hypotheses. The specialty should move toward prospective models, carefully considering the clinical impact and cost-effectiveness of potential interventions.

The "Tool-First" Trap: Pushed by a publish-or-perish academic culture, researchers may make the mistake of starting with an AI model or radiomics pipeline and then searching for a problem to which to apply it. True clinical impact more likely comes with starting with the patient problem and finding the appropriate method to solve it.

Combating Confirmation Bias: When researchers firmly believe their own clinical intuition, they risk designing studies solely to confirm their preconceived notions. To maintain scientific credibility, you should assign a colleague the specific role of opposing your views to actively try and prove your hypothesis wrong.

*Chapters

0:00 - Introduction

2:07 - What Clinical Intuition Means

6:47 - Daniel’s Routine to Research

9:23 - Ideas Hiding in Workflow

11:32 - From Observation to Study Plan

14:28 - Marco’s Prospective CT Example

18:26 - Avoiding Confirmation Bias

23:20 - AI Tool First Trap

29:53 - Quick Fire Takeaways

33:34 - Final Advice and Closing

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